Update README.md

README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+---
+
+
+
+<br>
+
+# ViG Model Card
+
+## Model Details
+
+ViG is a generic backbone trained on the ImageNet-1K dataset for vision tasks.
+
+- **Developed by:** [HUST](https://english.hust.edu.cn/), [Horizon Robotics](https://en.horizon.cc/)
+- **Model type:** A generic vision backbone based on the Gated Linear Attention (GLA) architecture.
+- **License:** Non-commercial license
+
+
+### Model Sources
+
+- **Repository:** https://github.com/hustvl/ViG
+- **Paper:** https://arxiv.org/abs/2405.18425
+
+## Uses
+
+The primary use of ViG is research on vision tasks, e.g., classification, segmentation, detection, and instance segmentation, with an GLA-based backbone.
+The primary intended users of the model are researchers and hobbyists in computer vision, machine learning, and artificial intelligence.
+
+
+## Training Details
+
+ViG is pretrained on ImageNet-1K with classification supervision.
+The training data is around 1.3M images from [ImageNet-1K dataset](https://www.image-net.org/challenges/LSVRC/2012/).
+See more details in this [paper](https://arxiv.org/abs/2405.18425).
+
+## Evaluation
+
+ViG is evaluated on ImageNet-1K val set, more details can be found in this [paper](https://arxiv.org/abs/2405.18425).
+
+## Additional Information
+
+## Citation Information
+
+```
+ @article{vig,
+  title={ViG: Linear-complexity Visual Sequence Learning with Gated Linear Attention},
+  author={Bencheng Liao and Xinggang Wang and Lianghui Zhu and Qian Zhang and Chang Huang},
+  journal={arXiv preprint arXiv:2405.18425},
+  year={2024}
+}
+```
+
+